• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.147-155
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• 2022

In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.

• Journal of Food Hygiene and Safety
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• v.38 no.4
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• pp.255-263
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• 2023

The standards for heavy metal levels in crustaceans are 0.5 mg/kg and 1.0 mg/kg or lower for lead and cadmium, respectively. Further, the contamination levels of arsenic, mercury, methyl mercury, and tin are being continuously investigated, considering their current exposure levels. Shrimps are potentially exposed to heavy metals because they inhabit areas with abundant organic matter, such as sandy or muddy shores, places with a lot of seaweed, and estuaries. This study measured the monetary value of reducing consumer anxiety and increasing consumer confidence if the government prohibits the sale of shrimp species that exceed the threshold for specific heavy metals and of the top shrimp species for which no threshold for heavy metals is specified. We derived consumer willingness-to-pay (WTP). Combining the estimated WTP with the number of households in the country, the total value of benefits was estimated to be 363.9 billion won. The results of this study will provide an important empirical finding, showing to what extent specific policies regarding heavy metals in seafood can alleviate consumer anxiety and provide psychological reassurance.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.73-80
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• 2010

A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.

• Nuclear Engineering and Technology
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• v.25 no.4
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• pp.529-538
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• 1993

A stochastic way using continuous time Markov process is presented to model the one-dimensional nuclide transport in fractured rock matrix as an extended study for previous work ［1］. A nuclide migration model by the continuous time Markov process for single planar fractured rock matrix, which is considered as a transient system where a process by which the nuclide is diffused into the rock matrix from the fracture may be no more time homogeneous, is compared with a conventional deterministic analytical solution. The primary desired quantities from a stochastic model are the expected values and variance of the state variables as a function of time. The time-dependent probability distributions of nuclides are presented for each discretized compartment of the medium given intensities of transition. Since this model is discrete in medium space, parameters which affect nuclide transport could be easily incorporated for such heterogeneous media as the fractured rock matrix and the layered porous media. Even though the model developed in this study was shown to be sensitive to the number of discretized compartment showing numerical dispersion as the number of compartments are decreased, with small compensating of dispersion coefficient, the model agrees well to analytical solution.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• Korea Trade Review
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• v.42 no.4
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• pp.93-114
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• 2017

Under the FTA agreement, preferential tariffs between FTA members will result in tariff reductions. In order to ensure the stable use of the FTA tariff system, it is necessary for the customs authorities to determine whether the origin goods are clearly applicable. This study analyzed the procedure of appeal according to the origin verification system based on the decision made by Korea Customs Service and Tax Tribunal. From this, we examined whether the rate of re-claiming a case rejected in the 'Review System of the Legality Before Taxation' differs. In addition, we carried out a quantitative analysis using bootstrapping technique in order to overcome the scarcity cases of verification of origin among FTA members. The implications of this paper are summarized as follows: First, we tested the hypothesis that the re-claiming rate of Western countries is higher. Second, some issues represented higher re-claiming rate. Third, there was no significant difference between the verification group and the re-claiming rate. Finally, even if an applicant makes a claim again, there is a possibility of being rejected again.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.791-799
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• 2008

To build the system which has high utilization and usefulness for users, it is necessary to know the information type and use-demand that the use want. The purpose of this study is to forecast the preference and demand of utilization for bus information when bus information is offered through cellular phon. The accomplishments of this research are as follow : Firstly, importance on the level of individual factor and the value of change's figure can be evaluated, using preference analysis on bus information by conjoint analysis. Secondly, by establishing the use-demand model bus information using binary logit model, influence factor on whether or not the use of the user. Finally, ordered probit model was built by use behavior model in payment per call or per month of potential user of bus information. Through call times and sensitive analysis by payment methods, elasticity point, optimal payment fee, and use probability was analyzed. This study make application as basic to efficient bus information policy and to improve use rate of bus information in future because this study make it possible to get preference analysis, use-demand analysis and estimation of optimal payment fee which is reflecting various requirement in use of bus information user.

• Journal of Bio-Environment Control
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• v.32 no.3
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• pp.190-196
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• 2023

This study was carried out to collect gas emitted from agricultural heaters using kerosene and to identify the emission concentration of carbon dioxide according to the age of agricultural heating machine. As a result of the linear regression analysis, the carbon dioxide emissions according to the year of agricultural heating machine are R² = 0.84, which follows y = 26.99x+721.98. Distributed analysis was classified into three groups according to the age of agricultural heating machine. As a result of the distributed analysis, it was 2.196×10^-13, which was smaller than the 0.05 probability set for the analysis, which means that there is a difference in at least one group. As a result, the age of the agriculture machine was divided into three groups and the difference between groups was tested. A statistical analysis result was derived that there was a difference in the emission concentration of carbon dioxide according to the age of agricultural heating machine. It is thought that it can be used to investigate greenhouse gas emissions by investigating the amount of carbon dioxide generated by agricultural heaters in the agricultural field of Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.1-9
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• 2006

An analysis of the annual frequency of collapse(AF) is performed for each bridge pier exposed to ship collision. From this analysis, the impact lateral resistance can be determined for each pier. The bridge pier impact resistance is selected using a probability-based analysis procedure in which the predicted annual frequency of bridge collapse, AF, from the ship collision risk assessment is compared to an acceptance criterion. The analysis procedure is an iterative process in which a trial impact resistance is selected for a bridge component and a computed AF is compared to the acceptance criterion, and revisions to the analysis variables are made as necessary to achieve compliance. The distribution of the AF acceptance criterion among the exposed piers is generally based on the designer's judgment. In this study, the acceptance criterion is allocated to each pier using allocation weights based on the previous predictions. To determine the design impact lateral resistance of bridge components such pylon and pier, the numerical analysis is performed iteratively with the analysis variable of impact resistance ratio of pylon to pier. The design impact lateral resistance can vary greatly among the components of the same bridge, depending upon the waterway geometry, available water depth, bridge geometry, and vessel traffic characteristics. More researches on the allocation model of AF and the determination of impact resistance are required.

• Journal of the Korea Computer Graphics Society
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• v.28 no.4
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• pp.31-40
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• 2022

This study assumed two key parameters that describe smoothness. Previously, the number of studies that defined smoothness with the concept of curvature has been limited. The parameters were the two physical characteristics of curvature: the number of waves and the amplitude of them. The purpose of the study was to observe which of the two parameters influences the perception of smoothness and to examine the relationship between the sense of aesthetic beauty and smoothness. The visual stimuli used in the study were transformed three-dimensional spheres, based on the combination of the three levels of the two parameters of nine distinct conditions. We analyzed the three responses that measured the preference of each visual stimuli, the familiarity score, and the smoothness evaluation score, each with the linear mixed model whose fixed effects were the two parameters and random effects were the participants' individual differences. Nearly the eighty percent of the variance of the smoothness evaluation score was explained by the linear model with the two key parameters and their interaction. The physical characteristics of a viewed object were far more significant than individual differences such as personality factors and the manner of art appreciation. In conclusion, the study examined the perception of smoothness based on the change of the physical characteristics of a shape. The study further recognized the relationship between smoothness and the aesthetic preference. No significant influence of the participants' individual difference such as gender, the degree in fine arts, personality factors, and the manner of art appreciation was observed. The amplitude of waves, rather than the number of them, was far more significant to the perception of smoothness.